Geon Technologies, LLC — Department of Defense SBIR Phase I: N193-A01

Description

Incorporating features from multimodal representations has shown to produce more robust imaging capabilities than traditional single-mode approaches. To improve autonomous tasks with Unmanned Aircraft Systems (UAS), we plan to develop a multimodal image processing Machine Learning (ML) framework comprised of a Deep Neural Network (DNN) paradigm that provides an alternative prediction system with confidence and credibility metrics. The Deep k-Nearest Neighbor (DkNN) technique is used to assess the outputs of intermediate layers in a DNN to perform classification and evaluate the credibility of its decisions, producing a confidence metric that is more reliable yet more robust against adversarial attacks than traditional DNNs. The DkNN approach is supplemented with data fusion techniques to improve robustness and to further mitigate the disadvantages of single-mode approaches.